3.9 Article Proceedings Paper

Systemic inflammatory response syndrome score at admission independently predicts mortality and length of stay in trauma patients

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LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/00005373-200010000-00011

Keywords

systemic inflammatory response syndrome; trauma; outcome; injury; severity of illness

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Background: Recent studies have documented that the systemic inflammatory response syndrome (SIRS) score is a useful predictor of outcome in critical surgical illness, The duration and severity of SIPS are associated with posttrauma multiple organ dysfunction and mortality, We sought to determine whether the severity of SIRS at admission is an accurate predictor of mortality and length of stay (LOS) in trauma patients. Methods: Prospective data of 4,887 trauma admissions to a Level I trauma center over a 18-month period (January 1997 to July 1998) were analyzed, Patients were stratified by age and Injury Severity Score (ISS), and a SIPS severity score (1 to 4) was calculated at admission (1 point for each component present: fever or hypothermia, tachypnea, tachycardia, and leukocytosis), The SIRS score was evaluated as an independent predictor of mortality and LOS by chi(2) and multivariate logistic regression. Results: Trauma patients (n = 4,887, 83% blunt injuries, 72% male) had the following characteristics: 73.1% were age 18 to 45 years, 17.5% were age 46 to 65 years, and 9.4% were age greater than or equal to 66 years; 77.7% had ISS less than 15, 18.8% had ISS 16 to 29, and 3.5% had ISS greater than 29, Analysis of variance adjusting for age and ISS determined that SIPS score of 2 was a significant predictor of LOS, Furthermore, the relative risk of death increased significantly with SIRS score of 2 when age and ISS were held constant. Conclusion: Logistic regression analysis confirmed that a SIRS score of 2 was a significant independent predictor of increased mortality and LOS in trauma patients. These data suggest that admission SIRS scoring in trauma patients is a simple tool that may be used as a predictor of outcome and resource utilization.

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